Year of Award
2025
Document Type
Thesis
Degree Type
Master of Science (MS)
Degree Name
Computer Science
Department or School/College
Computer Science
Committee Chair
Jesse Johnson
Commitee Members
Jesse Johnson, John Bardsley, John Hoglund, Lucy Owen
Keywords
aviation, wildfire, retardant, firefighting, fire
Subject Categories
Computer Sciences | Data Science | Natural Resources Management and Policy
Abstract
Aerial retardant drops are widely used in wildfire suppression, yet their effectiveness in slowing fire spread remains difficult to quantify at scale. This study evaluates the impact of aerial suppression on wildfire rate of spread (ROS) using a modeling framework that incorporates both observed (real) and counterfactual (synthetic) drop locations from a sample of 62 wildfires in Oregon. Synthetic drops were generated to simulate a no-suppression baseline, allowing us to compare changes in ROS in the presence and absence of suppression. We trained two random forest classifiers: one using both real and synthetic drops (the full model), and another using only synthetic drops to model baseline fire behavior. Both models used a range of environmental and topographic features to predict whether fire spread slowed following a drop. While the full model performed well in predicting ROS outcomes, the indicator distinguishing real from synthetic drops had low feature importance, suggesting limited causal evidence that aerial suppression efforts consistently reduced fire spread. The synthetic-only model produced similarly high predictive performance, reinforcing the possibility that many observed reductions in ROS may have occurred independent of suppression. These findings highlight the challenges of evaluating suppression effectiveness at scale and emphasize the need for improved data resolution, more detailed operational records, and advanced modeling techniques to fully understand the role of aerial fire retardant drops in future wildfire management activities.
Recommended Citation
Wiard, Lindsay Ann, "Investigating the Impact of Aerial Firefighting on Rate of Wildfire Spread" (2025). Graduate Student Theses, Dissertations, & Professional Papers. 12531.
https://scholarworks.umt.edu/etd/12531
Included in
Computer Sciences Commons, Data Science Commons, Natural Resources Management and Policy Commons
© Copyright 2025 Lindsay Ann Wiard